Saturday, 31 March 2018

As a child, I used to believe in endless linear progress. There were ever
higher buildings in the world, ever more TV channels, ever-faster computers
and spacecraft. Records were broken, numbers got bigger, the complexity of
everything increased. I saw this as the absolute good; actually, it was the
only thinkable way of how a universe could work. Pop culture products such
as Star Trek and Sid
Meier's Civilization enforced this dogma.

In my teens, I started to notice the dark sides. New computer programs
seldom showed progress in code quality anymore; on the contrary, it seemed
that the growing hardware specs were making developers lazy, indifferent and
incompetent. The way how tech media praised the growing clock rates started
to sound idiotic, and the ever-growing mass of people buying high-spec PCs
without even being interested in their deep internals was ever more
despicable.

As a response, I started to embrace an opposite kind of esthetic and
technological ideology: small is beautiful, bits are beautiful, hacks are
beautiful. True progress is about deepness and compression instead of
maximization and accumulation. Even apparently very simple structures may
yield unexpected complexity – of an emergent, "countercomplex" kind instead
of the "straightforwardly complex" kind.

At first, I took it mosty as a computer-related problem and a
computer-related battle. But then I started to realize its relevance to the
entire human technological civilization. Our economical-industrial system
basically has a resource
leak bug that most of us have learned to regard as a feature rather than
a bug. Fixing it requires an overall shift to a mentality that values
compression more than expansion and accumulation.

This is a kind of change that needs pioneers who experiment with more
compressed technologies and societies before the planetary conditions force
everybody to. I want to be among
them.

II

Over the past few years, I have been hanging out and living with people who
have interests and ambitions towards ecovillages, permaculture, appropriate
technology and the like. I have also been deepening my relationship with
natural processes by growing some edible plants on a field and gotten eer
more fascinated about various neo-lowtech and "off-the-grid" ways of
constructing dwellings, securing food production and holding up human
culture.

My parents had a small organic farm when I was a kid, so it was not an alien
world for me. However, when trying to learn about natural processes and
their grassroots-level application in my usual analytical way, I noticed
that I would have needed new tools to handle the complexity,
uncontrollability and uncertainty. My existing methods of building mental
models are not very good for learning about slow and complex natural
processes.

Basically, I have two major studying modes. One is the aforementioned
analytical mode I adopted when growing up with computer programming: get
down to the lowest level of abstraction (such as ones and zeros) and then
build up from there, layer by layer. If the mode does not seem effective, I
tend to switch to the opposite mode that resembles the way how I explored my
childhood forests: forget the strictness, just let your intuition guide your
trial-and-error experiments. I was also studying neural networks at the
time, making me even more anxious about the ineffectivity and limits of
blocky intellectual analysis. I did not entirely realize that I would have
needed some kind of an intermediate mode.

The trial-and-error mode is not problematic per se, it just needs a lot of
cycles. After getting lost often enough in the same forest, a map gradually
forms in the mind without any systematic mapping effort. Years ago, when
learning to cook, I tried to find some kind of a theoretical ruleset of how
the different ingredients and processes work but couldn't find any. So, I
just went on with trial-and-error and let an intuitive "ruleset" form
organically in my head, and I think I'm an okayish cook nowadays. When
experimenting with the likes of plant-growing, however, the cycle is far too
long for effective learning, so it needs decades to build a decent intuition
about it.

Back in the seventies, computer hackers such as Ted Nelson advocated
computers as a means of learning about how the world works. Simplified
models of various real-world systems could be simulated by computer
programs, allowing people to use the trial-and-error learning method to grow
intuitive understanding about them. When trying to absorb the wisdom of Bill
Mollison's Permaculture Designer's Manual, I started to hunger after a
simulator where I could try to implement all kinds of crazy ideas in order
to test them against the theory. Additionally, as a simulator like this
would be necessarily based on knowable mathematics, I would also be able to
use my analytical mode with it.

III

I have now been working for some time on this kind of "world simulator". Its
work title is "Ovys", from the Finnish for "self-sufficient community
simulator". It will be more like a game, a learning toy or an imagination
assistant than a serious design/modelling tool, but I hope it will
eventually end up being useful for some real-world planning as well. I also
dream about coupling it with a machine learning system that could discover
low-tech ideas from the blind spots of human visionaries.

I will write more about Ovys once it is closer to the first prototype stage.
Anyway, it currently simulates solar radiation, airflow and heat transfer in
various materials in a 3D grid world. After the first prototype (and perhaps
some crowdfunding), I plan to implement the likes of the water cycle, plant
growth, nutrient cycles and human agents at least in some kind of a
"minecrafty" way that can be improved in later versions by other people.

As a game, one might describe it as a realism-oriented reimagination of
Dwarf Fortress. Some day, one might perhaps even describe it as a
realism-oriented reimagination of Civilization.